International Workshop on Data-driven Modeling and Optimization in Fluid Mechanics
The event focuses on the application of artificial intelligence, machine learning, deep learning, evolutional algorithms and adjoint-based optimization to fluid dynamics-related problems with special focus on turbulent flows and flow control.
In particular, the event aims to
- provide an opportunity for young researchers to update their knowledge on the application of data-driven methods and be inspired with new ideas;
- establish a forum for exchange of ideas between the experts using these methods in different applications;
- initiate collaboration and strengthen interdisciplinary research
The workshop is organised under the patronage of the "MathSEE" Centre of the Karlsruhe Institut of Technology by
Dr. Pourya Forooghi, Karlsruhe Institute of Technology pourya.forooghi∂kit.edu
Dr. Davide Gatti, Karlsruhe Institute of Technology davide.gatti∂kit.edu
Dr. Mathias Krause, Karlsruhe Institute of Technology mathias.krause∂kit.edu
Dr. Alexander Stroh, Karlsruhe Institute of Technology alexander.stroh∂kit.edu
Workshop: 16-17 September 2019
Speaker's registration deadline: 10 August 2019
Attendee registration deadline: 31 August 2019 (due to limited number of seats, early registration is encouraged)
Venue and Travel Direction
The workshop will be held in the South Campus of the Karlsruhe Institute of Technology, located in the city centre of Karlsruhe in Rudolf-Plank lecture hall Bulding 40.32 (Engler-Bunte-Ring 21, 76131 Karlsruhe).
You can find the location on the map below.
Further information can be found here.
The event consists of several plenary talks. The talks will be held in workshop or research seminar format. The list of invited speakers and the titles of the talks are as follow:
Dr. O. Buxton Imperial College London
Title: Multi-scale triple decompostion of multi-scale generated flows usning data-driven techniques
Prof. Y. Hasegawa University of Tokyo
Title: Reconstruction of Turbulent Velocity and Scalar Field Based on Limited Measurements
Prof. P. Koumoutsakos ETH Zürich
Title: Machine learning for fluid mechanics modeling and control
Dr. S. Lerch Karlsruhe Institute of Technology
Title: Probabilistic modeling with machine learning methods
Prof. I. Mortazavi CNAM Paris / Dr. S. Edwige Plastic Omnium
Title: Data assimilation using cross-analysis on experiments and CFD for car aerodynamic optimization
Prof. B. Noack LIMSI, CNRS, Université Paris-Saclay
Title: Turbulence control - Better, faster and easier with machine learning
Prof M. Quadrio Politecnico di Milano
Title: Machine learning and fluid mechanics in biological applications
Dr. J. Riesterer Karlsruhe Institute of Technology
Title: Gaussian process regression for heterogeneous measuring networks of environmental data
Prof. P. Schlatter KTH Stockholm
Title: Data driven wall turbulence: UQ and structures
Prof. V. Schulz Universität Trier
Title: Shape optimization for aerodynamic design
Prof. R. Vinuesa KTH Stockholm
Title: Predictions in turbulent shear flows using deep neural networks
The scientific program can be downloaded here.
Registration to the workshop is free of charge. However, the number of participants is limited by the capacity of the rooms and our budget. Therefore we kindly ask you to register by sending an email to workshop∂istm.kit.edu with DMOFM as subject. Please indicate your generalities and affiliation in the body of the email.
The workshop is sponsored by
- KIT-centre MathSEE
- DFG Priority Program 1881
- DFG Colaborative Research Center/Transregio 150
The organisation of workshop is supported by Institute of Fluid Mechanics and Latice-Boltzmann Research Group at KIT.